Evaluating Gesture Recognition in Virtual Reality

TL;DR

This paper discusses the evaluation of gesture recognition in virtual reality for human-robot interaction, focusing on challenges like data generation and standardization, and proposing a preliminary approach to address these issues.

Contribution

It introduces a method using virtual reality simulations to generate gesture data and proposes standard gestures for ground robots to improve benchmarking and standardization.

Findings

Virtual reality can effectively generate gesture data for HRI.

Standard gestures can facilitate benchmarking in robotic systems.

Preliminary results show promising consistency in gesture-command mapping.

Abstract

Human-Robot Interaction (HRI) has become increasingly important as robots are being integrated into various aspects of daily life. One key aspect of HRI is gesture recognition, which allows robots to interpret and respond to human gestures in real-time. Gesture recognition plays an important role in non-verbal communication in HRI. To this aim, there is ongoing research on how such non-verbal communication can strengthen verbal communication and improve the system's overall efficiency, thereby enhancing the user experience with the robot. However, several challenges need to be addressed in gesture recognition systems, which include data generation, transferability, scalability, generalizability, standardization, and lack of benchmarking of the gestural systems. In this preliminary paper, we want to address the challenges of data generation using virtual reality simulations and standardization issues by presenting gestures to some commands that can be used as a standard in ground robots.